The Rosalind Franklin Institute is national research institute, dedicated to developing new technologies to tackle important health research challenges. The spectrum of tools under development at the Franklin are individually extraordinary, but when combined at the Franklin's Hub, they allow us to develop tomorrow's healthcare innovations. Our technologies will enable the 'imaging of life in five dimensions' - that is, to see the molecules of life in the context of three-dimensional space, along with time and chemistry. We are currently focusing our multi-disciplinary research teams and technologies in development to the grand challenge problem of infection and the body's response to it. Such an institute has significant challenges when addressing the data and computation challenges that come with development of these next generation instruments, and this proposal looks to address the immediate challenges surrounding this and put the institutes data strategy on track to make the most of all the data collected at the Franklin. To make sure that this proposal is fit for purpose, and also delivering in value, the proposal was passed through 3 independent groups at the Franklin before submission (https://www.rfi.ac.uk/about/governance/): 1 Theme Advisory Panel (https://www.rfi.ac.uk/about/governance/theme-advisory-panels/) : This group looked to the proposal for technical suitability 2 - The Value for Money Panel : This group looked to the economic side of the proposal, and general structure of the proposal. 3 - RFI Board Ratification : The final approval to proceed came through the Franklin Board who had oversight of the previous panels information.

Abstracts are not currently available in GtR for all funded research. This is normally because the abstract was not required at the time of proposal submission, but may be because it included sensitive information such as personal details.

Structural biology has changed our understanding of life on the atomic scale. However, we still do not understand how molecules in the context of an organism carry out their functions well enough to understand how to treat complex diseases. Recent efforts to turn structural biology into a technique capable of looking at the structure of molecule within cells have led to a step change in approach and has led to an atomic scale understanding of molecules within tissues. However, for tissues, all-sample mapping under cryogenic conditions is still not possible meaning expanding the applications of structural cell biology to distinct processes in tissues is lacking. Current scanning electron microscopes (SEM) are optimised for tissue that has been fixed, resin-embedded and stained with heavy metals, where the requirement for charge mitigation and image optimisation for high resolution imaging is less challenging. In contrast, samples that have been vitrified for structural studies downstream are fully hydrated, and exhibit a high degree of image artefacts due to the remaining water content. The ability to image these samples with their native frozen-hydrated environment intact is still challenging, and requires new image acquisition methods to embed them as a routine tool for correlative multimodal imaging. As part of this proposal, we aim to optimise SEM imaging in our recently published multimodal workflow by implementing sparse and irregular optimised scanning routines to overcome the charge build up that occurs with standard imaging regimes. Our preliminary development work shows that such an approach can make a significant difference in the image quality of natively preserved cells and tissues, on an instrument which is integral to a structural biology workflow. This represents a step-change, where features of high relevance can be targeted, imaged with high fidelity and processed for subsequent analysis. Such an instrument will represent a transformative ability to image molecular processes in tissues, facilitating efforts to combat neurodegeneration, cardiomyopathies, liver disease and kidney dysfunction.

We propose to create the EPSRC Centre for Doctoral Training (CDT) in intelligent integrated imaging in healthcare (i4health) at University College London (UCL). Our aim is to nurture the UK's future leaders in next-generation medical imaging research, development and enterprise, equipping them to produce future disruptive healthcare innovations either focused on or including imaging. Building on the success of our current CDT in Medical Imaging, the new CDT will focus on an exciting new vision: to unlock the full potential of medical imaging by harnessing new associated transformative technologies enabling us to consider medical imaging as a component within integrated healthcare systems. We retain a focus on medical imaging technology - from basic imaging technologies (devices and hardware, imaging physics, acquisition and reconstruction), through image computing (image analysis and computational modeling), to integrated image-based systems (diagnostic and interventional systems) - topics we have developed world-leading capability and expertise on over the last decade. Beyond this, the new initiative in i4health is to capitalise on UCL's unique combination of strengths in four complementary areas: 1) machine learning and AI; 2) data science and health informatics; 3) robotics and sensing; 4) human-computer interaction (HCI). Furthermore, we frame this research training and development in a range of clinical areas including areas in which UCL is internationally leading, as well as areas where we have up-and-coming capability that the i4health CDT can help bring to fruition: cancer imaging, cardiovascular imaging, imaging infection and inflammation, neuroimaging, ophthalmology imaging, pediatric and perinatal imaging. This unique combination of engineering and clinical skills and context will provide trainees with the essential capabilities for realizing future image-based technologies. That will rely on joint modelling of imaging and non-imaging data to integrate diverse sources of information, understanding of hardware the produces or uses images, consideration of user interaction with image-based information, and a deep understanding of clinical and biomedical aims and requirements, as well as an ability to consider research and development from the perspective of responsible innovation. Building on our proven track record, we will attract the very best aspiring young minds, equipping them with essential training in imaging and computational sciences as well as clinical context and entrepreneurship. We will provide a world-class research environment and mentorship producing a critical mass of future scientists and engineers poised to develop and translate cutting-edge engineering solutions to the most pressing healthcare challenges.

A famous biochemist, Arthur Kornberg, won the Nobel Prize for his work on the mechanisms by which DNA copies itself from cell to cell, generation to generation. But, he was acutely aware that whilst DNA (and by association, RNA) are the blueprint, the true vocation of life lies in the actions of the machines that are described in the nucleic acid blueprint, the proteins. To truly understand living processes, we need to gain a detailed quantitative understanding of the protein world. And, just as the field of genomics has transformed our knowledge of DNA, so an equivalent field of 'proteomics' has hugely advanced our understanding of the protein world. The core technology in proteomics is based on sophisticated mass spectrometers, capable of analysing one million millionths of a gram of peptide in exquisite detail (we use peptides as the proxy molecule for their parent proteins). But sophisticated as they are, mass spectrometers all have one intrinsic limitation - they give different signal intensities for different peptides from the same protein, even though they are in the same amount. Yet, to understand how a cell is the manifestation of the proteins it contains, we need to be able to measure exactly how many copies of any one protein there are. To overcome this limitation, we use accurately known standards that are co-analysed by the mass spectrometer, with the advantage that the standard and true cellular protein can be separately measured because we engineer the standard to be 'heavier' and thus discernible in the mass spectrometer. Thus, if we add 1000 molecules of a standard, and the cell component gives us a signal that is twice as large, we can confidently assert that the sample contains 2,000 copies of that protein. About 12 years ago, we invented a new method to generate large numbers of standards for quantitative proteomics. We created new 'designer proteins', never seen before on the planet, that could be made, in heavy form, by simple production in bacteria. These artificial proteins each contained peptide standards for up to 50 proteins. Because these proteins were pre-designed in terms of the proteins that were encoded within it, it meant that they were not always perfectly tuned to the needs of individual scientists. What was needed was the ability to 'build your own' designer protein. In this proposal, we have devised a way to do exactly this. In future, no matter what the system of interest, scientists will be able to 'dial up' their interesting proteins, and we will be able to assemble, 'a la carte' a protein standard. We will create a library of building blocks (we call them 'Qbricks', short for 'Quantification biobricks') and using advanced synthetic biology methods of DNA manipulation we will be able to create, in two days, the perfect standard protein for their research. We call these 'ALACATs' because of the 'à la carte' design philosophy. This is a revolutionary approach to absolute quantitative proteomics, and has huge potential to enhance our understanding of the protein world. This project will establish the core technology and methodologies, and build a set of Qbricks that will be used to create standards and research tools for the proteomics community. We will show how the ALACAT philosophy can be developed as a technical resource, readily drawn upon by many research groups, and thus, enabling a broad series of research programmes in a sustainable fashion.